The internet provides several sources of information which may be exploited. Internet news feeds and websites that allow users to interact with one another have exploded in popularity in the last few years. News feed channels such as CNN, social networking websites, such as Facebook or LinkedIn, and micro-blogging websites such as Twitter enjoy widespread use. Millions of users post messages, images, and videos on such websites on a daily, even hourly basis. Often, information gathered from these sources may refer to events taking place in real time.
Currently, there are personalized notification services that instantly may inform users about a new information matched with respect to a knowledge base and which may be related to an entity of interest. Said new information considered important and relevant may be notified via email, instant message, pager, or cell phone. The matching between the new information (where entities may be extracted and disambiguated) and the knowledge base may be based on a keywords alerts resource.
However, the conventional approach in the art related to alerts or notifications based on keywords may be problematic because references to named entities may be ambiguous and may result in many alerts that may not be on topic. Therefore, users may not want to get alerted on every entity of a given name, but just for new entities of the same name.
For the aforementioned reasons, there is a need for an improved method that allows users to be alerted regarding new knowledge of a disambiguated feature.